Bringing IoT, or in the case of the locomotive industry, industrial IoT, to locomotives is becoming more and more of a priority for companies like GE Transportation, a division of General Electric, who are looking to capitalize on a $900 billion transportation market in North America, $90 billion of which lies in railroads.

26,000 locomotives are currently in service around the continent, the longest of which is a 7.3 kilometer long train that is pulling 100 kilotons. Equipping each of these with industrial IoT edge devices is paramount. The data collected through those devices can be run through SAS analytics, providing all sorts of information that could save these transportation companies on fuel costs, operation costs, etc.

“The SAS component of all this is the analytics. IoT in the engines of locomotives can analyze if the engine is idling but still burning fuel. [Transportation companies] want the data on fuel usage because they can then save money and perfect the methods,” said Randy Guard, chief marketing officer at SAS to Canadian Press at the SAS Analytics Experience 2017.

GE Transportation uses SAS Event Stream Processing (ESP), which is a part of the wider SAS Platform, for the analytics portion of the solution it provides. The SAS software can be then be scaled, embedded, and deployed across the enterprise on small devices residing on the network’s edge to the cloud. GE Transportation to start will be rolling this out on 1,000 North American locomotives.

One of the challenges with bringing analytics to the edge on these devices is dealing with the simple fact that these devices aren’t stationary, as locomotives will be moving in and out of connected areas, whether that be a railyard, metro area, or rural area with no signal for kilometers.

“Our customers are really facing some big challenges as they deploy analytics out into their environments,” explained Garret Fitzgerald, general manager of transportation intelligence at GE Transportation. “This is not an environment like your data centre in a fixed location. As we think about deploying analytics to the edge, we are thinking not only of the outcomes, but how to do it in an effective way.”

Accomplishing the move to IoT on the edge is the priority, but figuring out how to do it in an efficient manner can be challenging. As Fitzgerald explains, the 10 million dollar benefit doesn’t mean anything if it costs 15 million to implement it.

“You can put the compute power on locomotives. You have to be able to come in and out of a connected area, so it’s computing with a vengeance. Lots of power, and we have done a lot of work to move SAS analytics to the edge,” Guard added.

But saving on costs isn’t the only benefit. The adoption of these IoT sensors can help transportation companies with added regulatory challenges. For instance, IoT can be used to enforce speeds in areas like turns and towns. This requires sensors all over the locomotive.

And this is just the beginning for IoT in the locomotive industry. After all, autonomous train operation is just over the horizon.